// how we work
Six promises that keep clients with us.
Every one of them is a refusal. That's deliberate — a promise about what we won't do is harder to fake than a claim about what we will.
No pitch-and-switch.
The senior partner who scopes your project is on it until it ships. You will not meet one team in the sales conversation and a different one on Monday.
No account managers.
You talk directly to the people building your software. Nothing gets relayed, summarised, or lost between you and the person writing the code.
No juniors learning on you.
We stay small on purpose. Senior people, or we don't take the work. Your project is not anybody's training exercise.
No surprise invoices.
We'd rather lose a margin than lose your trust. If something is going to cost more, you hear it before it's spent, not after.
No theater.
Short meetings, written decisions, working software. No status decks, no ceremony that exists to look like progress.
No vibecoding.
AI is a tool to ship faster — never a shortcut past review. Everything is verified by the same gates whether a person or a model wrote it.
// a sensible way to start
One service, end to end, in a short fixed window.
Rather than a long discovery phase or an open-ended retainer, the first engagement is scoped so you get a real answer quickly — and a working system either way.
We write the spec with your team
One or two working sessions. Your domain expert talks, we write it down precisely, and the result is a document both sides can read.
You review the spec
This is the decision point, and it's a document rather than a pull request. Being wrong here costs an edit, not a rewrite.
We generate, implement and ship it
Behind your existing gates, on your infrastructure, in your process.
Your engineers own it afterwards
The spec is the handover artefact. New people ramp on a readable document instead of reverse-engineering intent from handlers.
You end up with a working service and a concrete answer on whether a spec-first workflow suits how your team wants to work — before anyone commits to retooling around it.
// the quality bar
These are build failures, not review comments.
- Two test suites: unit, and end-to-end integration against a real database.
- 100% coverage enforced on both — statements, branches, functions and lines.
- Every operation must be exercised by at least one end-to-end scenario, checked by the compiler.
- Response schemas enforced at runtime, so the published API description can't drift from what the service actually returns.
Because most of the code is generated and its tests are generated with it. Full coverage isn't a heroic effort by the team — it's the default state of a compiled service, and it stays there as the service grows.
// what it means for your team
Leverage, not headcount reduction.
Backend teams usually grow because volume outpaces the people who can absorb it — more endpoints, more validation, more tests, more review, more knowledge stuck in one person's head. Headcount gets added to carry the volume, then more headcount to coordinate the first batch.
- Engineers work at the level they were hired for. Specs, domain decisions and judgment calls, rather than writing a fifth CRUD endpoint by hand and reviewing a sixth.
- Standards stop depending on seniority. Conventions, security rules and quality bars are encoded in a generator applied to every service, rather than living in one senior engineer's head.
- New hires ramp on the spec, not the codebase. A cross-linked document describing what the system does, instead of reconstructing intent from five thousand lines of handlers.
- Throughput stops depending on one person. Verified output ships continuously instead of queueing behind whoever understands the system best.
- Agent capacity turns into parallel work, not review burden. Which is the usual failure mode of adding AI to a team — output goes up and the bottleneck just moves to review.